Contrastive Response Pairs for Automatic Evaluation of Non-task-oriented Neural Conversational Models

Koshiro Okano, Yu Suzuki, Masaya Kawamura, Tsuneo Kato, Akihiro Tamura, Jianming Wu


Abstract
Responses generated by neural conversational models (NCMs) for non-task-oriented systems are difficult to evaluate. We propose contrastive response pairs (CRPs) for automatically evaluating responses from non-task-oriented NCMs. We conducted an error analysis on responses generated by an encoder-decoder recurrent neural network (RNN) type NCM and created three types of CRPs corresponding to the three most frequent errors found in the analysis. Three NCMs of different response quality were objectively evaluated with the CRPs and compared to a subjective assessment. The correctness obtained by the three types of CRPs were consistent with the results of the subjective assessment.
Anthology ID:
2021.sigdial-1.21
Volume:
Proceedings of the 22nd Annual Meeting of the Special Interest Group on Discourse and Dialogue
Month:
July
Year:
2021
Address:
Singapore and Online
Editors:
Haizhou Li, Gina-Anne Levow, Zhou Yu, Chitralekha Gupta, Berrak Sisman, Siqi Cai, David Vandyke, Nina Dethlefs, Yan Wu, Junyi Jessy Li
Venue:
SIGDIAL
SIG:
SIGDIAL
Publisher:
Association for Computational Linguistics
Note:
Pages:
202–207
Language:
URL:
https://aclanthology.org/2021.sigdial-1.21
DOI:
10.18653/v1/2021.sigdial-1.21
Bibkey:
Cite (ACL):
Koshiro Okano, Yu Suzuki, Masaya Kawamura, Tsuneo Kato, Akihiro Tamura, and Jianming Wu. 2021. Contrastive Response Pairs for Automatic Evaluation of Non-task-oriented Neural Conversational Models. In Proceedings of the 22nd Annual Meeting of the Special Interest Group on Discourse and Dialogue, pages 202–207, Singapore and Online. Association for Computational Linguistics.
Cite (Informal):
Contrastive Response Pairs for Automatic Evaluation of Non-task-oriented Neural Conversational Models (Okano et al., SIGDIAL 2021)
Copy Citation:
PDF:
https://aclanthology.org/2021.sigdial-1.21.pdf
Video:
 https://www.youtube.com/watch?v=Wtma3lm9AMc